PyTorch Jobs in London

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PyTorch Jobs in London

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Looking for top PyTorch jobs in London? Haystack connects skilled AI and machine learning professionals with leading tech companies hiring PyTorch developers across the city. Explore the latest PyTorch job openings in London and take your career to the next level today!

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AI Automation Engineer

AI Automation Engineer | Hybrid 3 days a week in office | London | PermanentA leading financial services client in London is seeking a talented AI Automation Engineer to join their team. Please see below for key details.Role Overview: Analyse and optimise business processes for automation whilst designing, building, and deploying intelligent automation solutions using BPA platforms (Appian), Machine Learning, and Generative AI to drive operational efficiency and innovation.Key Characteristics:

Process Analysis & Optimisation - Expert in analysing existing business processes through stakeholder interviews, process mapping, and workflow documentation to identify automation opportunities. Skilled in creating process flow diagrams, conducting time-motion studies, identifying bottlenecks and inefficiencies, and redesigning processes to be machine-readable and automation-ready using methodologies.

Python Development - Strong proficiency in Python programming including object-oriented design, asynchronous programming, error handling, and writing clean, maintainable code. Experience with key libraries including Pandas, NumPy for data manipulation, requests and APIs for integrations, asyncio for concurrent processing, and building robust automation scripts with proper logging, testing (pytest), and documentation.

AI & Machine Learning Frameworks - Deep expertise in AI/ML frameworks including TensorFlow, PyTorch, Scikit-learn, and Hugging Face Transformers. Experience building, training, and deploying machine learning models for classification, regression, clustering, and NLP tasks. Understanding of model evaluation metrics, hyperparameter tuning, feature engineering, and MLOps practices for production deployment.

Generative AI & LLM Integration - Proficient in working with Large Language Models including OpenAI GPT models, Anthropic Claude, Azure OpenAI, and open-source alternatives (Llama, Mistral). Experience with prompt engineering, fine-tuning, RAG (Retrieval Augmented Generation) architectures, vector databases (Pinecone, ChromaDB, FAISS), embeddings, and building AI-powered automation solutions that leverage natural language understanding.

Appian BPA Platform - Strong experience with Appian low-code platform including process modelling, interface design, expression rules, integration objects, and data modelling. Skilled in building end-to-end business process applications, configuring workflows, implementing business rules, managing records, and integrating Appian with external systems via REST APIs, web services, and connected systems.

API Development & Integration - Proficient in designing and building RESTful APIs using FastAPI, Flask, or Django REST Framework for exposing AI models and automation services. Experience with API authentication (OAuth, JWT), rate limiting, error handling, API documentation (Swagger/OpenAPI), webhooks, and integrating disparate systems to create seamless automated workflows.

Document Processing & OCR - Experience implementing intelligent document processing solutions using OCR technologies (Tesseract, Azure AI Document Intelligence, natural language processing for information extraction, document classification, and building end-to-end pipelines for automated document ingestion, processing, and data extraction with validation rules.

Robotic Process Automation (RPA) - Knowledge of RPA concepts and tools (UiPath, Automation Anywhere, Power Automate) for automating repetitive tasks, screen scraping, and Legacy system integration. Ability to assess when RPA vs. API integration vs. AI solutions are most appropriate, and experience building hybrid automation solutions combining multiple technologies.

Data Engineering & Pipeline Development - Strong skills in building data pipelines for AI/automation solutions including data extraction, transformation, and loading (ETL). Experience with SQL databases (SQL Server), data validation, cleansing workflows, scheduling tools (Azure Data Factory), and ensuring data quality for machine learning applications.

Machine Learning Operations (MLOps) - Experience deploying ML models to production environments using containerisation (Docker), orchestration (Kubernetes), model versioning (MLflow, DVC), monitoring model performance and drift, A/B testing frameworks, and implementing CI/CD pipelines for automated model training and deployment. Understanding of model governance, explainability, and compliance requirements.

Solution Architecture & Technical Design - Ability to design end-to-end automation architectures that combine multiple technologies (BPA, ML, GenAI, APIs) into cohesive solutions. Experience creating technical design documents, system architecture diagrams, assessing build vs. buy decisions, estimating effort and complexity, and presenting technical recommendations to both technical and non-technical stakeholders.

Stakeholder Collaboration & Change Management - Excellent communication skills for gathering requirements from business users, translating business needs into technical specifications, and demonstrating proof-of-concepts. Experience managing stakeholder expectations, conducting user acceptance testing, providing training on automated solutions, measuring automation ROI through KPIs (time saved, error reduction, cost savings), and driving adoption of intelligent automation across the organisation.

If you align to the key requirements then please apply with an updated CV.

Senior Data Scientist

Senior Data Scientist - Customer Data Salaries in the region of £70,000 - £85,000 DoE Hybrid working - 2/3 days central London office Job Reference J13015Full UK working rights required/no sponsorship availableImmediate requirement - strong leadership skillsWe are seeking for an experienced, passionate and highly motivated Data Scientist who will help discover the information hidden in vast amounts of customer data, and help make data driven decisions to deliver better products, service and relevance to the customers.Not specifically managing others, but management of your own workload, taking initiative to mould the role into your own and come with a pragmatic mindset.The role Lead development of machine learning solutions for CRM personalization. Build and optimize recommendation engines using neural networks and deep learnings, incorporating product embeddings and other advanced features to improve relevance and performance. Collaborate with CRM and regional marketing teams to align with campaign goals and customer segmentation strategies Own the full ML lifecycle-from model design to deployment and monitoring. Partner with engineering and data teams to ensure scalable solutions. Continuously monitor and improve model performance using data insights and feedback.SkillsProven experience in machine learning, particularly in recommendation systems and deep learning architectures. Strong understanding of two-tower neural networks, embedding techniques, and ranking models. Proficiency in Python with familiarity to ML libraries e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch) Familiarity with cloud platforms (GCP, AWS, Azure) and tools like Dataiku. Experience with ML Ops, including model deployment, monitoring, and retraining pipelines. Ability to work cross-functionally with marketing, CRM, and engineering teams. Excellent communication and stakeholder management skills Experience in a global or multi-regional context is a plusIf you would like to hear more, please do get in touch.Alternatively, you can refer a friend or colleague by taking part in our fantastic referral schemes! If you have a friend or colleague who would be interested in this role, please refer them to us. For each relevant candidate that you introduce to us (there is no limit) and we place, you will be entitled to our general gift/voucher scheme.Datatech is one of the UK’s leading recruitment agencies in the field of analytics and host of the critically acclaimed event, Women in Data. For more information, visit our website: www.datatech.org.uk

Senior Machine Learning Engineer

£55,000 - 65,000 GBPHybrid WORKINGLocation: Central London, Greater London - United Kingdom Type: PermanentSenior Machine Learning Engineer - National Security (London, Hybrid) Salary: Up to £65,000 per year + £7,000 DV clearance bonus (tax-free, subject to eligibility) Working Model: Hybrid - 3 days on client site once clearance is granted, 1 day in central office, remainder remoteA leading UK national security-focused technology organisation is seeking a Senior Machine Learning Engineer to join its AI team. You will design, develop, and deploy ML models and LLM/GenAI solutions to solve real-world national security challenges. This is a highly innovative, collaborative, and impactful environment where you will apply cutting-edge machine learning methods to unique datasets.Key responsibilities:

Lead and contribute to ML projects, including forecasting, classification, anomaly detection, and LLM/GenAI applications.

Design experiments, formulate hypotheses, evaluate results, and iterate rapidly to validate approaches.

Transition experimental models into production-ready solutions, collaborating with engineers on deployment, monitoring, and optimisation.

Build and maintain ML pipelines using AWS services and modern MLOps/LLMOps tooling.

Implement robust versioning, experiment tracking, and reproducibility practices.

Mentor junior engineers and contribute to team-wide AI knowledge sharing.

Communicate complex technical concepts to both technical and non-technical stakeholders.

Ideal candidate:

BSc, MSc, or PhD in a quantitative discipline (e.g., Maths, Physics, Computer Science).

4-5 years’ experience in ML/AI engineering or data science roles (senior level).

Hands-on experience with Python ML frameworks (scikit-learn, PyTorch, TensorFlow, XGBoost).

Experience with AWS ML services (SageMaker, Lambda, S3) and MLOps/LLMOps tooling (MLflow, Weights & Biases, DVC).

Proven track record transitioning models from experimentation to production with governance and quality controls.

Experience developing LLM/GenAI solutions and familiarity with LLMOps tools.

Strong problem-solving, communication, and project delivery skills.

Eligible for UK DV security clearance; candidates without clearance must be able to undergo the process.

Why this role is unique:

Work on national security projects with niche datasets unavailable elsewhere.

Influence AI adoption from the ground floor for high-profile government clients.

Join a collaborative team of over 4,000 digital, cyber, and intelligence specialists across multiple locations.

Hybrid working flexibility, generous benefits, career development support, and a culture valuing diversity and inclusion.

For further information, feel free to reach me at 02895213213, or simply apply!

AI/ML Architect

Stott & May Professional Search Limited

AI / ML Architect Location: London (Hybrid - 2 days/week onsite) Duration: 6 months Day Rate: £510 per day (Inside IR35) Role Overview We are seeking an experienced AI / ML Architect to design, build, and lead the deployment of advanced machine learning and AI-driven solutions. The successful consultant will enable real-world value from data by architecting models, pipelines, and integration patterns that scale across the organisation. This role combines technical depth, applied ML engineering, solution design, and hands-on development. Key Responsibilities

Design, build, and train end-to-end machine learning models across NLP, predictive analytics, classification, and computer vision use cases

Experiment with algorithms, optimise hyperparameters, and evaluate model performance

Collect, process, and prepare structured and unstructured datasets for model training and validation

Implement feature engineering, data augmentation, and data quality controls

Develop APIs, services, or microservices to integrate models into production platforms

Deploy, monitor, and manage models using MLOps tooling, automation, and versioning practices

Analyse performance metrics (accuracy, precision, recall, F1-score) and optimise models for scalability and efficiency

Collaborate with product teams, engineers, and data scientists to translate business requirements into technical solutions

Document architectures, workflows, and methodologies to ensure reproducibility and maintainability

Stay current on emerging AI technologies including generative models, reinforcement learning, and transformer-based architectures

Profile & Required Expertise

10+ years software engineering experience, including 5+ years in applied AI/ML

Advanced proficiency in Python, PyTorch, TensorFlow, and modern NLP frameworks

Hands-on experience with LLMs, transformer architectures, LangChain, and Hugging Face

Strong knowledge of algorithms, machine learning lifecycles, and model evaluation techniques

Deep understanding of BFSI environments including risk, compliance, and AML/KYC

Practical experience with cloud platforms (AWS/Azure/GCP) and containerisation (Docker/Kubernetes)

Experience building scalable ML systems and secure, production-grade applications

Proven ability to work collaboratively in cross-functional teams

Strong communication skills with the ability to present technical concepts to non-technical stakeholders

Demonstrated ability to write clear documentation and apply engineering best practices

Desirable Experience

Ability to align ML strategies with long-term business and platform objectives

Familiarity with emerging trends in generative AI, RAG workflows, or reinforcement learning

Experience influencing architecture decisions at enterprise scale

Senior Data Scientist

Lead data science projects from scoping to deployment

Apply ML and statistical methods across varied data types

Collaborate with ML engineers to productionise models

Communicate insights to technical and non-technical stakeholders

Mentor junior team members

Skillset:

Strong Python and ML libraries (scikit-learn, PyTorch, pandas, NumPy)

Experience with AWS cloud services (SageMaker, Lambda, S3)

Familiarity with MLOps tools (MLflow, Weights & Biases)

Knowledge of NLP, computer vision, or time-series analysis

Ability to design experiments and apply statistical validation

Understanding of Responsible AI principles and model explainability

Ready to take your data science expertise to the next level and make a real-world difference? Apply today.Reference: AMC/JWH/DSLB1#jawh

AI Engineer required for an exciting permanent opportunity working alongside an established SaaS business developing innovative AI-powered platforms servicing the property industry. As an AI Engineer you will develop, advance and maintain cutting edge AI capabilities across the clients products. You will also be involved in architecting scalable AI systems and collaborate closely with cross-functional stakeholders to translate business objectives into AI-driven solutions. As part of a small AI/ ML dedicated team (sitting in the tech & product function), you will have a significant contribution to the design, development, and implementation of advanced AI/ML models, frameworks, and systems. A notable part of the role involves building, training, and optimising machine learning models, including deep learning computer vision models, and fine-tuning natural language processing (NLP), and integrating third party generative AI models. Ideal background: • 3+ years of experience in machine learning, deep learning or AI engineering • Advanced proficiency in Python and ML frameworks like PyTorch • Experience deploying and maintaining scalable production-grade AI systems • Strong understanding of data pipelines, MLOps and cloud platforms (AWS) • Experience working in small or mid-sized tech/ software development environments (rather than in corporate environments) would be advantageous The role requires demonstrable ability to make impactful suggestions, propose and present ideas and engage at all levels within an organisation. The business operates on flexible working model – ideally 1 day per month onsite however would consider fully remote (UK based) for the right individual. If the role seems to match your skill set and experience, please apply for immediate consideration

Senior Data Scientist

Senior Data Scientist - Customer Data Salaries in the region of £70,000 - £85,000 DoE Hybrid working - 2/3 days central London office Job Reference J13015 Full UK working rights required/no sponsorship available Immediate requirement - strong leadership skills We are seeking for an experienced, passionate and highly motivated Data Scientist who will help discover the information hidden in vast amounts of customer data, and help make data driven decisions to deliver better products, service and relevance to the customers. Not specifically managing others, but management of your own workload, taking initiative to mould the role into your own and come with a pragmatic mindset. The role • Lead development of machine learning solutions for CRM personalization. • Build and optimize recommendation engines using neural networks and deep learnings, incorporating product embeddings and other advanced features to improve relevance and performance. • Collaborate with CRM and regional marketing teams to align with campaign goals and customer segmentation strategies • Own the full ML lifecycle-from model design to deployment and monitoring. • Partner with engineering and data teams to ensure scalable solutions. • Continuously monitor and improve model performance using data insights and feedback. Skills • Proven experience in machine learning, particularly in recommendation systems and deep learning architectures. • Strong understanding of two-tower neural networks, embedding techniques, and ranking models. • Proficiency in Python with familiarity to ML libraries e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch) • Familiarity with cloud platforms (GCP, AWS, Azure) and tools like Dataiku. • Experience with ML Ops, including model deployment, monitoring, and retraining pipelines. • Ability to work cross-functionally with marketing, CRM, and engineering teams. • Excellent communication and stakeholder management skills • Experience in a global or multi-regional context is a plus If you would like to hear more, please do get in touch. Alternatively, you can refer a friend or colleague by taking part in our fantastic referral schemes! If you have a friend or colleague who would be interested in this role, please refer them to us. For each relevant candidate that you introduce to us (there is no limit) and we place, you will be entitled to our general gift/voucher scheme. Datatech is one of the UK’s leading recruitment agencies in the field of analytics and host of the critically acclaimed event, Women in Data. For more information, visit our website: (url removed)

Senior Data Scientist

£50,000-65,000 GBP Hybrid WORKING Location: Central London, Greater London - United Kingdom Type: Permanent A leading UK digital, cyber and intelligence organisation is hiring a Senior Data Scientist to work on high-impact AI projects within the national security domain. This role is ideal for someone who enjoys applied AI, complex data, and delivering real-world solutions. The Role Lead and deliver AI/ML solutions across text, imagery, audio, video and geospatial data Work closely with ML engineers, project managers and government customers Scope AI use cases, contribute to bids, and present findings to technical and non-technical audiences Mentor junior data scientists and help shape AI best practice Requirements Strong experience in AI, machine learning and statistics Python expertise (e.g. pandas, NumPy, scikit-learn, PyTorch, transformers) Experience deploying models and working with cloud platforms (AWS preferred) Ability to communicate complex technical concepts clearly Desirable AWS services (SageMaker, ECS, Lambda, S3, Bedrock) MLOps / ML engineering experience (Docker, MLflow) Experience in government or regulated environments Practical experience applying LLMs Security Clearance UKIC DV eligible required £7,000 tax-free DV bonus on completion (TBC, paid quarterly) Location London-based hybrid role Up to 3 days per week onsite at customer location once cleared 1 day per week team day in the London office (counts as onsite) Benefits Flexible working and strong work-life balance 25 days’ holiday plus buy/sell options Pension, bonus scheme and flexible benefits Structured career development support Apply directly or message for more information on this Senior Data Scientist role. Reference: AMC/AQI/SDS Postcode: EC3 #aoqu TPBN1_UKTJ

Senior Data Scientist

£65,000 GBPHybrid WORKINGLocation: Central London, Greater London - United Kingdom Type: PermanentAn exciting opportunity has arisen for an experienced Senior Data Scientist to work at the forefront of artificial intelligence and machine learning, delivering high-impact digital solutions that contribute to the safety and security of the UK.This role sits within a specialist AI and data science team supporting a range of government and national security clients. The team delivers work across defence, space and public sector organisations, spanning exploratory research, advanced analytics, bespoke AI solutions and large-scale data platforms operating on complex and sensitive datasets.The RoleThe Senior Data Scientist position offers significant variety and challenge. The successful candidate will work with both technical and non-technical stakeholders, applying advanced AI, machine learning and statistical techniques across diverse data types, including text, images, audio, video, graphs, time-series and geospatial data.Responsibilities will include shaping future AI initiatives with customers, researching and evaluating emerging AI approaches, and delivering robust, production-ready solutions. The role combines hands-on technical delivery with customer engagement, thought leadership and mentoring.Key Responsibilities

Acting as a senior technical authority for AI and data science, contributing expertise across projects, bids and stakeholder discussions

Leading and delivering complex machine learning and AI projects in collaboration with ML engineers, delivery teams and customers

Engaging with users to define requirements, scope AI use cases and develop realistic delivery plans

Supporting the design, development and deployment of models within AWS cloud environments

Contributing to written proposals and bid responses, including research into relevant academic and industry literature

Presenting technical findings and insights to internal teams and external stakeholders

Mentoring junior data scientists and graduates, supporting capability growth

Promoting AI knowledge across multidisciplinary teams and representing the organisation through blogs, events and conferences

About the CandidateThe ideal candidate will demonstrate strong depth and breadth across data science, AI and machine learning, alongside the ability to translate complex technical concepts into practical, business-focused outcomes.Essential experience includes:

Degree (BSc, MSc or PhD) in a quantitative or scientific discipline such as computer science, mathematics, physics or engineering

Several years’ experience working as a Data Scientist or in a closely related role

Expert knowledge of machine learning, AI and statistical methods, applied across domains such as NLP, computer vision, audio, graphs, time-series or tabular data

Strong Python skills and experience with common libraries (e.g. pandas, NumPy, scikit-learn, PyTorch, Transformers, statsmodels, PyMC)

Understanding of software engineering and ML best practices, including version control, packaging and model deployment

Experience training and deploying models using cloud platforms, particularly AWS

Ability to communicate complex ideas clearly to both technical and non-technical audiences

Commitment to high-quality, ethical and robust scientific work

Awareness of ethical, privacy, security and policy considerations in applied AI

Desirable Experience

Hands-on experience with AWS services such as Lambda, ECS, S3, SageMaker or Bedrock

Knowledge of ML engineering and MLOps practices (e.g. Docker, MLflow)

Experience working in government, defence or other highly regulated environments

Proven application of large language models (LLMs) to real-world problems

Security ClearanceThis role requires UK Security Clearance. Applicants must either already hold clearance or be eligible and willing to undergo the vetting process.

Senior Data Scientist

This is an exciting time to join a team to help pioneer both customer’s and own an AI adoption journey. Not only will you be directly making a huge impact through the solutions you develop, youll be doing it for an organisation who makes a huge impact to the security of the UK.Core dutiesBeing a key technical point-of-contact for AI and data science expertise, sharing knowledge across meetings, bids and technical projects.Leading and working on technical AI projects, working with ML engineers, project managers and non-technical customers.Meeting with users to help scope out ongoing and future AI projects, understanding use-cases and planning out delivery plans which capture the subtleties of the requirements.Working alongside ML engineers to help build and deploy models into products across our AWS cloud servicesAssisting with writing bid responses to customer problems, often requiring diving into the literature surrounding complex technical concepts in AI, ML and statistics.Presenting results of technical work both internally and to our customers.Helping mentor and manage junior team members and graduates across the business.Helping to educate others across the business in AI and related methods through collaborative work (including software engineers, leadership, non-technical consultants) and presenting to wider communities via blogs, events and conferences.About YouBSc (or MSc / PhD) in a quantitative, scientific discipline (e.g. maths, physics, computer science or similar).Expert knowledge of AI, ML and statistical methods, and their application across some of the following domains (e.g. NLP, images, audio, graphs, time series, tabular data).Several years experience working as a data scientist in industry or similar environment.Good knowledge of python, along with common machine learning and data analysis libraries (e.g. pandas, numpy, scikit-learn, pytorch, transformers, statsmodels, pymc).Ability to absorb complex new scientific concepts and quickly get up to speed on new areas of the literature.Good understanding of software and ML engineering best-practices (e.g. git, package development, model deployment).Ability to present complex technical concepts to both technical and non-technical colleagues.Passion for good quality scientific work and a focus on truthfulness, robustness and customer/stakeholder requirements.Experience with utilising cloud services (e.g. AWS) for training and deploying models.Understanding of the ethical, privacy, security and policy concerns relevant to the application of AI/ML.It Would Be Great If You Also Had Experience In Some Of These, But If Not Well Help You With ThemGood knowledge of AWS cloud services (e.g. Lambda, ECS, Bedrock, S3, Sagemaker)ML Engineering and MLOps knowledge (e.g. Docker, ML flow)Experience working with government or other carefully regulated industriesTrack record of applying LLMs to robustly solve real problemsSecurity Clearance is required for this vacancy. If you are not currently Security Cleared, you will need to be eligible for this and willing to go through the process.How We Will Support YouWork-life balance is important; you can work around core hours with flexible and part-time workingYoull get 25 days holiday a year and the option to buy/sell and carry over from the year beforeOur flexible benefits package includes a competitive pension scheme, cycle to work scheme, taste cards and moreYoull have a dedicated Career Manager to help you develop your career and guide you on your journey through BAEYoull be part of our company bonus schemeYou are welcome to join any/all of our Diversity and Support groups. These groups cover everything from gender diversity to mental health and wellbeing.

MLOps Tech Lead

Stackstudio Digital Ltd.

Job DetailsRole / Job Title:MLOps Tech LeadWork Location:London, UKOffice Requirement (Hybrid):2 days per weekKey Responsibilities (High-Level) Data Pipeline Development: Lead the technical direction of projects and ensure the use of Sainsbury’s best practices to the best quality. Data Integration: Lead and provide expertise on Integrate data from various sources, ensuring data consistency, integrity, and quality across the entire data lifecycle. Infrastructure Management: Provide guidance for the junior & Mid Data Engineers on the best practices when building and managing data infrastructure, including data lakes, warehouses, and distributed processing systems (e.g., PySpark, Hadoop).The RoleAs a Tech Lead, you will play a critical role in designing, building, and maintaining data pipelines and infrastructure that enable the development and deployment of machine learning models and drive engineering excellence. You will collaborate closely with data scientists, and lead ML engineers, and software engineers to ensure data is clean, accessible, and optimised for large-scale processing and analysis.Your Responsibilities Data Pipeline Development: Lead the technical direction of projects and ensure the use of Sainsbury’s best practices to the best quality. Data Integration: Lead and provide expertise on Integrate data from various sources, ensuring data consistency, integrity, and quality across the entire data lifecycle. Infrastructure Management: Provide guidance for the junior & Mid Data Engineers on the best practices when building and managing data infrastructure, including data lakes, warehouses, and distributed processing systems (e.g., PySpark, Hadoop). Data Preparation: Collaborate with data scientists to prepare and transform raw data into formats suitable for machine learning, including feature engineering and data augmentation. Automation: Implement automation tools and frameworks (CI/CD) to streamline the deployment and monitoring of machine learning models in production. Performance Optimisation: Optimise data processing workflows and storage solutions to improve performance and reduce costs. Collaboration: Work closely with cross-functional teams, including data science, engineering, and product management, to deliver data solutions that meet business needs. Mentorship: junior and mid-level data engineers and provide technical guidance on best practices and emerging technologies in data engineering and machine learning and helping to enhance their skills and career growth. Knowledge Sharing and Empowerment: Promote a culture of knowledge sharing within the engineering teams by organising regular technical workshops, brown bag sessions, and code reviews. Innovation and Continuous Improvement: Foster a collaborative and inclusive team environment that encourages continuous learning and improvement.Your ProfileEssential Skills / Knowledge / Experience Knowledge of machine learning frameworks (e.g., PySpark, PyTorch) and model deployment tools (e.g., MLflow, TensorFlow Serving). Strong experience with data processing frameworks (e.g., Apache Spark, Flink). Expertise in SQL and NoSQL databases (e.g., MySQL, PostgreSQL, MongoDB, Cassandra). Hands-on experience with cloud platforms (e.g., AWS, GCP, Azure) and their data services (e.g., Snowflake, S3, BigQuery, Redshift). Experience with containerisation and orchestration tools (e.g., Docker, Kubernetes). Familiarity with version control systems (e.g., Git) and CI/CD pipelines.Desirable Skills / Knowledge / Experience Certifications: AWS Certified Big Data Specialty, Google Professional Data Engineer, or equivalent.Soft Skills: o Excellent problem-solving and analytical skills. o Strong communication skills, with the ability to explain complex technical concepts to non-technical stakeholders. o Ability to work independently and in a team-oriented, collaborative environment.Leadership and Communication Strong leadership skills with the ability to inspire and guide team. Lead scrum ceremonies as and when needed (Standup, Planning, and grooming sessions). Excellent verbal and written communication skills, with the ability to articulate complex technical concepts. Creating a safe and inclusive environment where all team members feel that their input is valued and are never dissuaded from speaking up or asking questions.Collaborative Attitude Strong team player with a collaborative approach to working with cross-functional teams within the Media Agency. Open to feedback and willing to provide constructive criticism to others. Be available for the team, responding within a reasonable time frame and if not possible clearly sign positing alternative contacts who can guide. Building a community across Media Agency. Contribute to a positive and inclusive atmosphere within the team.Knowledge Sharing and Empowerment Commitment to fostering a learning culture within the team and ensuring knowledge transfer across all levels. Support and mentor C3s and C4s engineers by providing them opportunities to lead initiatives and contribute to the technical roadmap.

MLOps Tech Lead

Stackstudio Digital Ltd.

Job Details Role / Job Title: MLOps Tech Lead Work Location: London, UK Office Requirement (Hybrid): 2 days per week Key Responsibilities (High-Level) Data Pipeline Development: Lead the technical direction of projects and ensure the use of Sainsbury’s best practices to the best quality.Data Integration: Lead and provide expertise on Integrate data from various sources, ensuring data consistency, integrity, and quality across the entire data lifecycle.Infrastructure Management: Provide guidance for the junior & Mid Data Engineers on the best practices when building and managing data infrastructure, including data lakes, warehouses, and distributed processing systems (e.g., PySpark, Hadoop). The Role As a Tech Lead , you will play a critical role in designing, building, and maintaining data pipelines and infrastructure that enable the development and deployment of machine learning models and drive engineering excellence. You will collaborate closely with data scientists, and lead ML engineers, and software engineers to ensure data is clean, accessible, and optimised for large-scale processing and analysis. Your Responsibilities Data Pipeline Development: Lead the technical direction of projects and ensure the use of Sainsbury’s best practices to the best quality.Data Integration: Lead and provide expertise on Integrate data from various sources, ensuring data consistency, integrity, and quality across the entire data lifecycle.Infrastructure Management: Provide guidance for the junior & Mid Data Engineers on the best practices when building and managing data infrastructure, including data lakes, warehouses, and distributed processing systems (e.g., PySpark, Hadoop).Data Preparation: Collaborate with data scientists to prepare and transform raw data into formats suitable for machine learning, including feature engineering and data augmentation.Automation: Implement automation tools and frameworks (CI/CD) to streamline the deployment and monitoring of machine learning models in production.Performance Optimisation: Optimise data processing workflows and storage solutions to improve performance and reduce costs.Collaboration: Work closely with cross-functional teams, including data science, engineering, and product management, to deliver data solutions that meet business needs.Mentorship: junior and mid-level data engineers and provide technical guidance on best practices and emerging technologies in data engineering and machine learning and helping to enhance their skills and career growth.Knowledge Sharing and Empowerment: Promote a culture of knowledge sharing within the engineering teams by organising regular technical workshops, brown bag sessions, and code reviews.Innovation and Continuous Improvement: Foster a collaborative and inclusive team environment that encourages continuous learning and improvement. Your Profile Essential Skills / Knowledge / Experience Knowledge of machine learning frameworks (e.g., PySpark, PyTorch) and model deployment tools (e.g., MLflow, TensorFlow Serving).Strong experience with data processing frameworks (e.g., Apache Spark, Flink).Expertise in SQL and NoSQL databases (e.g., MySQL, PostgreSQL, MongoDB, Cassandra).Hands-on experience with cloud platforms (e.g., AWS, GCP, Azure) and their data services (e.g., Snowflake, S3, BigQuery, Redshift).Experience with containerisation and orchestration tools (e.g., Docker, Kubernetes).Familiarity with version control systems (e.g., Git) and CI/CD pipelines. Desirable Skills / Knowledge / Experience Certifications: AWS Certified Big Data Specialty, Google Professional Data Engineer, or equivalent. Soft Skills:o Excellent problem-solving and analytical skills.o Strong communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.o Ability to work independently and in a team-oriented, collaborative environment. Leadership and Communication Strong leadership skills with the ability to inspire and guide team.Lead scrum ceremonies as and when needed (Standup, Planning, and grooming sessions).Excellent verbal and written communication skills, with the ability to articulate complex technical concepts.Creating a safe and inclusive environment where all team members feel that their input is valued and are never dissuaded from speaking up or asking questions. Collaborative Attitude Strong team player with a collaborative approach to working with cross-functional teams within the Media Agency.Open to feedback and willing to provide constructive criticism to others.Be available for the team, responding within a reasonable time frame and if not possible clearly sign positing alternative contacts who can guide.Building a community across Media Agency.Contribute to a positive and inclusive atmosphere within the team. Knowledge Sharing and Empowerment Commitment to fostering a learning culture within the team and ensuring knowledge transfer across all levels.Support and mentor C3s and C4s engineers by providing them opportunities to lead initiatives and contribute to the technical roadmap.TPBN1_UKTJ

Senior Data Scientist

£55,000 - 65,000 GBPHybrid WORKINGLocation: Central London, Greater London - United Kingdom Type: PermanentSenior Data Scientist - National Security (London, Hybrid) Salary: Up to £65,000 per year + £7,000 DV clearance bonus (tax-free, subject to eligibility) Working Model: Hybrid - 3 days on client site once clearance is granted, 1 day in central office, remainder remoteA leading UK national security-focused technology organisation is seeking a Senior Data Scientist to join its AI team. You will work with complex, unique datasets to deliver AI and machine learning solutions that directly support critical national security objectives. This is a rare opportunity to apply cutting-edge data science in a highly innovative, collaborative, and impactful environment.Key responsibilities:

Lead and contribute to AI and ML projects across diverse data types (text, images, audio, video, graphs, geo-location).

Engage with stakeholders to scope projects, understand use cases, and plan technically robust delivery strategies.

Collaborate with ML engineers to build, deploy, and maintain models using cloud services (AWS).

Conduct research, literature reviews, and provide technical guidance to shape solutions.

Present complex technical concepts to both technical and non-technical audiences.

Mentor junior team members and support the broader team in AI adoption and knowledge sharing.

Ideal candidate:

BSc, MSc, or PhD in a quantitative discipline (e.g., Maths, Physics, Computer Science).

Strong expertise in AI, ML, and statistical methods applied across multiple domains (NLP, vision, audio, time series, tabular data).

Proficient in Python and relevant ML/data science libraries (e.g., pandas, numpy, scikit-learn, PyTorch, transformers).

Experience with cloud-based model deployment (AWS) and ML engineering best practices.

Excellent communication, problem-solving, and project delivery skills.

Eligible for UK DV security clearance; candidates without clearance must be able to undergo the process.

Why this role is unique:

Work on national security projects using niche datasets unavailable elsewhere.

Influence the adoption of AI from the ground floor for high-profile clients.

Join a collaborative team of over 4,000 digital, cyber, and intelligence specialists across multiple locations.

Hybrid working flexibility, with generous benefits, career development support, and a culture valuing diversity and inclusion.

For further information feel free to reach me at 02895213213, or simply apply! Reference: AMC/RKI

Senior Data Scientist

£50,000 to 60,000 GBP bonus Hybrid WORKING Location: Central London, Greater London - United Kingdom Type: Permanent Senior Data Scientist - London / Hybrid Up to £65,000 + DV Bonus | SC Eligible / DV Eligble Required | No Sponsorship We are looking for a Senior Data Scientist to join a leading organisation delivering cutting-edge AI and machine learning solutions with real-world impact. You will work on diverse projects across national security and healthcare-related sectors, applying AI/ML techniques to solve complex challenges. This is a London-based role with hybrid working support. Key Responsibilities: Lead and contribute to AI and ML projects, working closely with engineers, project managers, and non-technical stakeholders. Act as a technical point of contact, sharing expertise in AI/ML methods across projects and bids. Scope, plan, and deliver AI solutions, including model development, deployment, and evaluation. Mentor junior team members and support their professional growth. Present results and insights to both technical and non-technical audiences. Contribute to internal knowledge-sharing and best practices in AI/ML. Requirements: BSc, MSc, or PhD in a quantitative, scientific, or technical discipline (e.g., computer science, mathematics, physics). Strong expertise in AI, ML, and statistical methods, with experience across domains such as NLP, images, audio, graphs, time series, and tabular data. Several years’ experience as a data scientist in industry or related environments. Proficiency in Python and common ML/data libraries (e.g., pandas, numpy, scikit-learn, PyTorch, transformers). Understanding of software and ML engineering best practices (git, package development, model deployment). Experience with cloud platforms, particularly AWS, for training and deploying models. Ability to communicate complex technical concepts to diverse audiences. Eligible for DV security clearance; sponsorship cannot be provided. Desirable: Knowledge of AWS services (e.g., Lambda, ECS, Bedrock, S3, SageMaker). Experience with ML engineering and MLOps (e.g., Docker, MLflow). Experience in regulated industries or government-related projects. Applying LLMs or advanced AI methods to real-world problems. Benefits: Competitive salary up to £65,000 plus DV clearance bonus. Hybrid working with flexibility around core hours. 25 days holiday plus buy/sell/carry over options. Pension scheme and other flexible benefits. Opportunity to work on high-impact AI/ML projects. Reference: AMC-AQU-SDSB Postcode: EC2V 6AA #adqu TPBN1_UKTJ

Machine Learning Engineer

ML Engineer - Must hold active DV Clearance This is an exciting time to join a team to help pioneer both customer’s and an AI adoption journey. Not only will you be directly making a huge impact through the solutions you develop, youll be doing it for an organisation who makes a huge impact to the security of the UK. Core Duties Design and develop machine learning models for traditional ML use cases (forecasting, classification, anomaly detection) and GenAI/LLM applications Lead experimentation cycles: define hypotheses, design experiments, evaluate results, and iterate rapidly while adhering to governance requirements Transition validated experiments into production-ready solutions, working closely with other engineers on deployment and monitoring Build and optimise ML pipelines using AWS services and experiment tracking tools Develop and integrate LLM-powered solutions for tracing, evaluation, and production monitoring Implement robust experiment tracking, model versioning, and reproducibility practices with full audit trails Design feature engineering approaches and contribute to feature store development Support production models through monitoring, performance analysis, and continuous improvement Apply responsible AI practices, including model explainability and fairness assessment Present experiment findings and production outcomes to stakeholders, articulating operational and strategic value Mentor junior colleagues and share learnings across the team You will have experience in many of the following: Hands-on experience developing and deploying ML models in Python using frameworks such as scikit-learn, XGBoost, PyTorch, or TensorFlow Strong experience with AWS ML services (SageMaker, Lambda, S3) in production environments Strong experiment design skills: hypothesis formulation, A/B testing methodology, and statistical evaluation Proven track record transitioning models from experimentation to production with appropriate governance and quality controls Experience with experiment tracking and MLOps tooling (MLflow, Weights & Biases, Data Version Control) It Would Be Great If You Also Had Experience In Some Of These, But If Not Well Help You With Them Experience with advanced LLM techniques: agents, tool use, and agentic workflows Experience with vector databases (Pinecone, Weaviate, pgvector) for RAG applications Experience with feature stores (Feast, AWS Feature Store) Experience with containerisation (Docker) and orchestration (Kubernetes, ECS) TPBN1_UKTJ

Senior Data Scientist

£45,000 - £65,000 GBP £7,000 DV Bonus Hybrid WORKING Location: Central London, Greater London - United Kingdom Type: Permanent Role: Senior Data Scientist Area : National Security Projects Location: London (Hybrid) - 3 days per week Security : Eligibility for Developed Vetting Clearance with the UK Government Salary: Up to £65k + £7k annual DV bonus (once obtained) About the Role: This is a unique opportunity to apply advanced data science in the national security domain. You’ll work with highly sensitive, complex dataset s that you won’t find anywhere else, solving problems that have a direct impact on UK security. Expect variety: one day you’ll be scoping new AI projects with stakeholders, the next you’ll be building models for text, image, or geospatial data, and later presenting findings to senior decision-makers. You’ll influence strategy, mentor junior colleagues, and help shape how AI is adopted across critical missions. If you want to combine technical depth with meaningful impact, this is the role for you. What You’ll Do: Lead data science projects from scoping to deployment Apply ML and statistical methods across varied data types Collaborate with ML engineers to productionise models Communicate insights to technical and non-technical stakeholders Mentor junior team members Skillset: Strong Python and ML libraries (scikit-learn, PyTorch, pandas, NumPy) Experience with AWS cloud services (SageMaker, Lambda, S3) Familiarity with MLOps tools (MLflow, Weights & Biases) Knowledge of NLP, computer vision, or time-series analysis Ability to design experiments and apply statistical validation Understanding of Responsible AI principles and model explainability Ready to take your data science expertise to the next level and make a real-world difference? Apply today. Reference: AMC/JWH/DSLB1 #jawh TPBN1_UKTJ

Machine Learning Engineer

£45,000 - £65,000 GBP £7,000 DV Bonus Hybrid WORKING Location: Central London, Greater London - United Kingdom Type: Permanent Title: Machine Learning Engineer Area : National Security Projects Location: London (Hybrid) - 3 days per week Security : Eligibility for Developed Vetting Clearance with the UK Government Salary: Up to £65k + £7k annual DV bonus (once obtained) About the Role: We’re seeking Machine Learning Engineers to design and deploy ML models for national security applications. You’ll work on GenAI, LLMOps, and traditional ML solutions using AWS infrastructure, unique datasets collaborating with data scientists and software engineers to build greenfield solutions. What You’ll Do: Build and optimise Machine Learning pipelines Develop LLM-powered solutions and apply responsible AI practices Transition experiments into production-ready solutions Implement experiment tracking and monitoring Collaborate with data scientists and engineers What We’re Looking For: Proficiency in Python and ML frameworks (scikit-learn, PyTorch, TensorFlow) Hands-on experience with AWS ML services (SageMaker, Lambda) Familiarity with containerisation (Docker) and orchestration (Kubernetes/ECS) Knowledge of LLMOps and GenAI tools (LangChain, LangSmith) Understanding of feature engineering and vector databases Strong grasp of CI/CD practices for ML deployment Why Join Us: Work with niche datasets and cutting-edge tech Hybrid working and flexible benefits £7k tax-free DV bonus once clearance completes Apply today and make a real-world impact. Reference: AMC/JWH/MLEL1 #jawh TPBN1_UKTJ

AI Engineer - Contract

AI Engineer – Contract (x2) Rate: £700 per day Contract Length: 3–6 months Location: Flexible / Hybrid (depending on candidate) Morela is supporting an exciting AI startup in the search for two highly skilled AI Engineers with strong Python expertise to support the delivery of a key AI project. These are hands-on contract roles suited to engineers who enjoy building, optimising, and deploying AI solutions in a fast-moving environment. You’ll work closely with product, data, and engineering teams to design and implement machine learning models, contribute to production-ready pipelines, and help scale AI capabilities across the business. Key Responsibilities: Design, build, and deploy machine learning models using Python Develop and optimise data pipelines and model training workflows Collaborate with cross-functional teams to translate requirements into technical solutions Support model evaluation, performance tuning, and monitoring in production Contribute to best practices around code quality, testing, and scalability Required Experience: Proven experience as an AI Engineer or Machine Learning Engineer Advanced Python skills with experience in ML frameworks (e.g. PyTorch, TensorFlow, scikit-learn) Strong understanding of machine learning algorithms and applied AI Experience deploying models into production environments Comfortable working in startup or fast-paced delivery environments This is a strong opportunity to join a growing AI startup at a key delivery phase, working on impactful projects and building production-grade AI solutions. If you’re interested or would like more details, please email me at (url removed)

Machine Learning Engineer

£65,000 GBP Onsite WORKING Location: Central London, Greater London - United Kingdom Type: Permanent An opportunity is available for an experienced Senior Machine Learning Engineer to design, build and operationalise advanced machine learning solutions that directly support UK national security objectives. This role sits within a multidisciplinary AI engineering environment, working closely with Data Scientists, Software Engineers, Product teams and government stakeholders. The Senior ML Engineer will own the journey from experimentation and hypothesis testing through to secure, production-grade deployment, using a modern AWS-based MLOps and LLMOps platform. The Role The successful candidate will balance rapid experimentation with production readiness, prototyping and validating machine learning and generative AI approaches while ensuring successful models integrate seamlessly into live operational systems. This is a high-impact role at a pivotal point in the adoption of AI, machine learning and large language models across critical national systems, offering the chance to deliver real-world outcomes at scale. Key Responsibilities Designing, developing and optimising machine learning models across traditional ML use cases (forecasting, classification, anomaly detection) and GenAI / LLM solutions Leading experimentation cycles, including hypothesis definition, experimental design, evaluation and iteration, while complying with governance standards Transitioning validated experiments into production-ready ML services, collaborating closely with engineering teams on deployment and monitoring Building scalable ML pipelines using AWS services and modern experiment tracking frameworks Developing and integrating LLM-powered capabilities for evaluation, tracing and production monitoring Implementing robust experiment tracking, model versioning and reproducibility, ensuring full auditability Designing feature engineering strategies and contributing to feature store development Monitoring live models, analysing performance and driving continuous improvement Applying responsible AI principles, including explainability, robustness and fairness Communicating experimental results and production outcomes to stakeholders, highlighting operational and strategic value Mentoring junior engineers and promoting best practices across the team About the Candidate The ideal candidate will bring strong hands-on experience in machine learning engineering, with the ability to translate experimental success into reliable, scalable systems. Essential experience includes: Commercial experience developing and deploying machine learning models in Python Proficiency with ML frameworks such as scikit-learn, XGBoost, PyTorch or TensorFlow Strong experience delivering ML solutions using AWS services (e.g. SageMaker, Lambda, S3) Expertise in experiment design, including hypothesis formulation, A/B testing and statistical evaluation Proven experience moving models from experimentation into production with appropriate governance and quality controls Hands-on experience with MLOps tooling such as MLflow, Weights & Biases or Data Version Control Practical experience building LLM / GenAI applications, including prompt engineering and retrieval-augmented generation (RAG) Familiarity with LLMOps frameworks such as LangChain, LangSmith or LangGraph Understanding of model validation, evaluation techniques and production monitoring Experience working in cross-functional teams from problem definition through to delivery Strong communication skills, with the ability to explain complex concepts to non-technical audiences Sound judgement in applying AI appropriately and recognising when non-AI approaches are more suitable Desirable Experience Advanced LLM techniques, including agents, tool use and agentic workflows Experience with vector databases (e.g. Pinecone, Weaviate, pgvector) Feature store technologies such as Feast or AWS Feature Store Containerisation and orchestration using Docker, Kubernetes or ECS Infrastructure as Code using Terraform or CloudFormation Large-scale data processing frameworks such as Spark or Dask Knowledge of data governance, compliance and regulated environments Experience delivering solutions within highly regulated industries such as government, finance or healthcare Security Clearance This role requires UK Security Clearance. Applicants must already hold clearance or be eligible and willing to undergo the vetting process. Reference: AMC/RHU/MLE #ryhu TPBN1_UKTJ

Senior Machine Learning Engineer

Senior Machine Learning Engineer London Are you a Senior ML Engineer who wants to build AI that genuinely matters? Our client is a leading digital technology organisation delivering AI, data, and software solutions to UK public sector and national security customers. They are expanding their machine learning capability and are seeking an experienced engineer to design, evaluate, and deploy production-grade ML and GenAI solutions in high-impact operational environments. What youll be doing: Design and build ML models across forecasting, classification, anomaly detection, and GenAI / LLM use casesLead experimentation cycles: hypothesis, evaluation, iteration, and validationTake successful ML approaches into production, including deployment and monitoringBuild and optimise ML pipelines on AWSDevelop LLM-powered solutions, including evaluation and observabilityApply strong MLOps practices: experiment tracking, versioning, and reproducibilityCommunicate findings clearly to technical and non-technical stakeholdersMentor junior engineers and contribute to team best practicesThis role is for you if you have: Strong Python ML experience (e.g. scikit-learn, XGBoost, PyTorch, or TensorFlow)Production experience with AWS ML services (e.g. SageMaker, Lambda, S3)Proven ability to move models from experimentation into live systemsExperience with MLOps tools (MLflow, Weights & Biases, DVC, or similar)Hands-on exposure to LLM / GenAI applications, including RAGNice to have: Experience with advanced LLM techniques (e.g. agents, tool use)Familiarity with vector databases and feature storesExperience with Docker, Kubernetes, or Infrastructure as CodeImportant: Security clearance required (or eligibility to obtain it).Benefits: Hybrid working with flexibility25 days holiday plus buy/sell optionsCompetitive pension, bonus, and benefitsStrong career development and mentoringOpportunity to work on mission-critical AI supporting UK securityOk, Im in whats next? Please apply with your latest CV.TPBN1_UKTJ

Data Science Engineer

My client is recruiting for a Data Science Engineer to design, develop, and deliver AI and analytics solutions aligned with the organisations Data & AI strategy.Key ResponsibilitiesEnd-to-end development of AI/ML solutions. MLOps practices: CI/CD, model monitoring, retraining. Use of open-source and enterprise tools (LangChain, Azure OpenAI, Databricks). Generative AI features: embeddings, RAG, AI agents. Clean, testable code with modern engineering practices. Align with enterprise architecture and governance. Collaborate with architects and stakeholders. Lifecycle management of models. Pilot emerging technologies.Experience & Skills2-4 years in production-level AI/ML delivery. Legal/professional services experience is a plus. AI/ML frameworks: PyTorch, TensorFlow, LangChain. Cloud: Azure (preferred), AWS, GCP. MLOps: CI/CD, model lifecycle, monitoring. Generative AI: LLMs, RAG, chat agents. Data engineering alignment: ETL, governance. Strong coding, communication, and collaboration skills. Strategic thinking, problem-solving, and stakeholder engagement.In accordance with the Employment Agencies and Employment Businesses Regulations 2003, this position is advertised based upon DGH Recruitment Limited having first sought approval of its client to find candidates for this position.DGH Recruitment Limited acts as both an Employment Agency and Employment Business

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Frequently asked questions

What types of PyTorch jobs are available in London?

London offers a variety of PyTorch jobs including roles such as Machine Learning Engineer, Deep Learning Researcher, AI Developer, Data Scientist, and Computer Vision Specialist.

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While experience with PyTorch is highly preferred, related experience in deep learning frameworks like TensorFlow can also be valuable depending on the employer.

Are there junior-level PyTorch positions available in London?

Yes, many companies offer entry-level and junior roles for candidates with foundational PyTorch skills and a strong background in machine learning or AI.

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Salaries vary based on role and experience, but generally range from £40,000 for junior roles to over £100,000 for senior and specialized positions.

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